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Relationship: 1984

Title

A descriptive phrase which clearly defines the two KEs being considered and the sequential relationship between them (i.e., which is upstream, and which is downstream). More help

Increase, Mutations leads to Increase, lung cancer

Upstream event
The causing Key Event (KE) in a Key Event Relationship (KER). More help
Downstream event
The responding Key Event (KE) in a Key Event Relationship (KER). More help

Key Event Relationship Overview

The utility of AOPs for regulatory application is defined, to a large extent, by the confidence and precision with which they facilitate extrapolation of data measured at low levels of biological organisation to predicted outcomes at higher levels of organisation and the extent to which they can link biological effect measurements to their specific causes.Within the AOP framework, the predictive relationships that facilitate extrapolation are represented by the KERs. Consequently, the overall WoE for an AOP is a reflection in part, of the level of confidence in the underlying series of KERs it encompasses. Therefore, describing the KERs in an AOP involves assembling and organising the types of information and evidence that defines the scientific basis for inferring the probable change in, or state of, a downstream KE from the known or measured state of an upstream KE. More help

AOPs Referencing Relationship

AOP Name Adjacency Weight of Evidence Quantitative Understanding Point of Contact Author Status OECD Status
Deposition of energy leading to lung cancer non-adjacent High Low Brendan Ferreri-Hanberry (send email) Open for citation & comment EAGMST Approved

Taxonomic Applicability

Latin or common names of a species or broader taxonomic grouping (e.g., class, order, family) that help to define the biological applicability domain of the KER.In general, this will be dictated by the more restrictive of the two KEs being linked together by the KER.  More help
Term Scientific Term Evidence Link
human Homo sapiens High NCBI
mouse Mus musculus High NCBI
rat Rattus norvegicus High NCBI

Sex Applicability

An indication of the the relevant sex for this KER. More help
Sex Evidence
Male High

Life Stage Applicability

An indication of the the relevant life stage(s) for this KER.  More help
Term Evidence
All life stages High

Key Event Relationship Description

Provides a concise overview of the information given below as well as addressing details that aren’t inherent in the description of the KEs themselves. More help

A mutation occurs when there is a change in the DNA sequence. In some cases, mutations are silent and do not cause any functional changes in the cell; in other cases, mutations may have catastrophic consequences.  If these errors occur in genes implicated in critical regulatory pathways such as DNA repair mechanisms, cell-cycle checkpoints, apoptosis, or telomere length genes, then the cells are generally more susceptible to carcinogenesis (Chen et al. 1990; Hei et al. 1994; Kronenberg et al. 1995; Zhu et al. 1996, NRC 1999). The result of disrupting these regulatory pathways is ultimately the abnormal accumulation of malignant cells that may lead to cancer. Lung cancer in particular may occur if catastrophic mutations occur in cells of the lung.

Evidence Collection Strategy

Include a description of the approach for identification and assembly of the evidence base for the KER. For evidence identification, include, for example, a description of the sources and dates of information consulted including expert knowledge, databases searched and associated search terms/strings.  Include also a description of study screening criteria and methodology, study quality assessment considerations, the data extraction strategy and links to any repositories/databases of relevant references.Tabular summaries and links to relevant supporting documentation are encouraged, wherever possible. More help

Evidence Map 2.0

ID Experimental Design Species Upstream Observation Downstream Observation Citation (first author, year) Notes

Evidence Map

Addresses the scientific evidence supporting KERs in an AOP setting the stage for overall assessment of the AOP. More help
Title First Author
Biological Plausibility
Dose Concordance
Temporal Concordance
Incidence Concordance
Biological Plausibility
Dose Concordance Evidence
Temporal Concordance Evidence
Incidence Concordance Evidence
Uncertainties and Inconsistencies
Addresses inconsistencies or uncertainties in the relationship including the identification of experimental details that may explain apparent deviations from the expected patterns of concordance. More help

Uncertainties and inconsistencies in this KER are as follows:

  1. Tumours often have many different mutations present, some at such low levels that they are very difficult to detect. This is an issue, as these low-level mutants may still play a significant role in tumour growth, relapse and resistance to therapy. There has been some improvement in detecting these mutations with new technologies such as consensus sequencing-based error-correction approaches (Salk et al. 2018).
  2. Opposing results were found for two studies examining TP53 mutations in lung tumours from New Mexico uranium miners. In an earlier study by Vahakangas (1992), lung tumours were examined from 19 underground miners exposed to an average of 111 WLM of radon. Seven of the tumours harboured a TP53 mutation, but none of the mutations were found to be G to T transversions in the coding strand of TP53. In contrast, a study by Taylor (1994) that examined TP53 mutations in lung tumours of 29 New Mexico uranium miners exposed to an average of 1,382 WLM of radiation found that 16 of the TP53 mutations were G to T transversions at codon 249. An in vitro study using normal human bronchial epithelial cells irradiated with alpha particles equivalent to 1,460 WLM (4 Gy) was also performed, mimicking the above studies. The resulting irradiated cells exhibited malignant characteristics such as distinct morphology, a high rate of mitosis, and an extended lifespan. The mutational analysis, however, was in agreement with the results from Vahakangas(1992) , as there were no G to T transversions found at codon 249 and codon 250 of TP53 (Hussain et al. 1997).  

Known modulating factors

This table captures specific information on the MF, its properties, how it affects the KER and respective references.1.) What is the modulating factor? Name the factor for which solid evidence exists that it influences this KER. Examples: age, sex, genotype, diet 2.) Details of this modulating factor. Specify which features of this MF are relevant for this KER. Examples: a specific age range or a specific biological age (defined by...); a specific gene mutation or variant, a specific nutrient (deficit or surplus); a sex-specific homone; a certain threshold value (e.g. serum levels of a chemical above...) 3.) Description of how this modulating factor affects this KER. Describe the provable modification of the KER (also quantitatively, if known). Examples: increase or decrease of the magnitude of effect (by a factor of...); change of the time-course of the effect (onset delay by...); alteration of the probability of the effect; increase or decrease of the sensitivity of the downstream effect (by a factor of...) 4.) Provision of supporting scientific evidence for an effect of this MF on this KER. Give a list of references.  More help

There are known modulating factors that affect the relationship between mutations and lung cancer. Overall, increasing age is correlated with more mutations (Tomasetti et al. 2013), and a higher incidence of cancer has been documented in those exposed to radiation at a younger age (Bijwaard et al. 2001). A direct relationship has also been established between the degree of tissue damage in the respiratory structures and the consumption of cigarettes (Auerbach et al. 1957). Furthermore, mutations linked to lung cancer are more common in specific groups of people. EGFR mutations have been found more frequently in non-smokers (Lim et al. 2009; Sanders and Albitar 2010; Paik et al. 2012; Cortot et al. 2014), adenocarcinoma patients (Lim et al. 2009; Sanders and Albitar 2010), and females (Lim et al. 2009; Cortot et al. 2014). In general, KRAS mutations are more common in smokers (Paik et al. 2012; Cortot et al. 2014); however, the KRAS G12D transition variant is more common in non-smokers, while the G12V transversion variant is more common in smokers (Paik et al. 2012). Patients with stage I NSCLC also tend to have more frequent mutations in KRAS compared to patients at a higher stage (Cortot et al. 2014). Although TP53 mutations are not associated with smoking status overall, G to T transversions were found to be more common in smokers (Cortot et al. 2014).

Domain of Applicability

A free-text section of the KER description that the developers can use to explain their rationale for the taxonomic, life stage, or sex applicability structured terms. More help

The domain of applicability applies to mammals, including rodents and humans.